sf_trees <- read_csv(here("data","sf_trees","sf_trees.csv"))
## Parsed with column specification:
## cols(
## tree_id = col_double(),
## legal_status = col_character(),
## species = col_character(),
## address = col_character(),
## site_order = col_double(),
## site_info = col_character(),
## caretaker = col_character(),
## date = col_date(format = ""),
## dbh = col_double(),
## plot_size = col_character(),
## latitude = col_double(),
## longitude = col_double()
## )
Refresh some skills for data wrangling & summary statistics using functions in the dplyr package.
Find the top 5 highest observations of trees by legal status, do some wrangling, make a graph.
top_5_status <- sf_trees %>%
count(legal_status) %>% # combines recognize groups, summarize, can list multiple levels
drop_na(legal_status) %>%
rename(tree_count = n) %>%
dplyr::relocate(tree_count) %>%
slice_max(tree_count, n=5)
Make a graph of top 5 observations by legal status
ggplot(data = top_5_status, aes(x=fct_reorder(legal_status,tree_count), y=tree_count))+
geom_col()+
labs(x = "Legal Status", y = "Tree Count")+
coord_flip()+
theme_minimal()
Only want to keep observations (row) for Blackwood Acacia trees
blackwood_acacia <- sf_trees %>%
filter(str_detect(species, "Blackwood Acacia")) %>% #from stringr package
select(legal_status, date, latitude, longitude)
ggplot(data = blackwood_acacia, aes(x=longitude, y=latitude))+
geom_point()
## Warning: Removed 27 rows containing missing values (geom_point).
sf_trees_sep <- sf_trees %>%
separate(species, into = c("spp_scientific", "spp_common"), sep = "::")
Example tidyr::unite
sf_trees_unite <- sf_trees %>%
unite("id_status", tree_id:legal_status, sep = "_cool!_")
st_as_sf() to convert latitude & longitude to spatial coordinates
blackwood_acacia_sp <- blackwood_acacia %>%
drop_na(longitude, latitude) %>%
st_as_sf(coords = c("longitude","latitude"))
# does not have an assigned coordinate ref system yet
st_crs(blackwood_acacia_sp) = 4326
ggplot(data = blackwood_acacia_sp)+
geom_sf(color="darkgreen")
Read in SF roads shapefile:
sf_map <- read_sf(here("data","sf_map","tl_2017_06075_roads.shp"))
st_transform(sf_map, 4326)
## Simple feature collection with 4087 features and 4 fields
## geometry type: LINESTRING
## dimension: XY
## bbox: xmin: -122.5136 ymin: 37.70813 xmax: -122.3496 ymax: 37.83213
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## Warning: `...` is not empty.
##
## We detected these problematic arguments:
## * `needs_dots`
##
## These dots only exist to allow future extensions and should be empty.
## Did you misspecify an argument?
## # A tibble: 4,087 x 5
## LINEARID FULLNAME RTTYP MTFCC geometry
## <chr> <chr> <chr> <chr> <LINESTRING [°]>
## 1 110498938… Hwy 101 S … M S1400 (-122.4041 37.74842, -122.404 37.748…
## 2 110498937… Hwy 101 N … M S1400 (-122.4744 37.80691, -122.4746 37.80…
## 3 110366022… Ludlow Aly… M S1780 (-122.4596 37.73853, -122.4596 37.73…
## 4 110608181… Mission Ba… M S1400 (-122.3946 37.77082, -122.3929 37.77…
## 5 110366689… 25th Ave N M S1400 (-122.4858 37.78953, -122.4855 37.78…
## 6 110368970… Willard N M S1400 (-122.457 37.77817, -122.457 37.7781…
## 7 110368970… 25th Ave N M S1400 (-122.4858 37.78953, -122.4858 37.78…
## 8 110498933… Avenue N M S1400 (-122.3643 37.81947, -122.3638 37.82…
## 9 110368970… 25th Ave N M S1400 (-122.4854 37.78982, -122.4858 37.78…
## 10 110367749… Mission Ba… M S1400 (-122.3865 37.77086, -122.3878 37.77…
## # … with 4,077 more rows
ggplot(data = sf_map)+
geom_sf()
Combine blackwood acacia tree observations & SF roads map:
ggplot()+
geom_sf(data= sf_map, size =0.1, color = "darkgray")+
geom_sf(data= blackwood_acacia_sp, color = "red", size=0.5)+
theme_void()
Now an interactive map:
tmap_mode("view")
## tmap mode set to interactive viewing
tm_shape(blackwood_acacia_sp) +
tm_dots()